Application Method of Unmanned Aerial Vehicle for Crop Monitoring in Korea |
Na, Sang-il
(National Institute of Agricultural Sciences, Rural Development Administration)
Park, Chan-won (National Institute of Agricultural Sciences, Rural Development Administration) So, Kyu-ho (National Institute of Agricultural Sciences, Rural Development Administration) Ahn, Ho-yong (National Institute of Agricultural Sciences, Rural Development Administration) Lee, Kyung-do (National Institute of Agricultural Sciences, Rural Development Administration) |
1 | Jeong, J.H., K.A. Choi, and I.P. Lee, 2014. Application plans through case analysis of maritime surveillance systems using UAVs, Proc. of 2014 Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Seoul, Apr. 24-25, pp. 205-209 (in Korean with English abstract). |
2 | Jordan, C.F., 1969. Derivation of leaf area index from quality of light on the forest floor, Ecology, 50(4): 663-666. DOI |
3 | Kim, D.I., Y.S. Song, G.H. Kim, and C.W. Kim, 2014. A Study on the application of UAV for Korean land monitoring, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 32(1): 29-38 (in Korean with English abstract). DOI |
4 | Kim, S.Y., J.H. Yu, S.M. Koh, G.S. Park, and J.H. Shin, 2016. Extraction of the mine information using Unmanned Aerial Vehicle, Proc. of the Annual Joint Conference of the Petrological Society of Korea and the Mineralogical Society of Korea, Busan, May 26-27. pp. 120. |
5 | Kim, Y.S., K.D. Lee, S.I. Na, S.Y. Hong, N.W. Park, and H.Y. Yoo, 2016. MODIS data-based crop classification using selective hierarchical classification, Korean Journal of Remote Sensing, 32(3): 235-244 (in Korean with English abstract). DOI |
6 | Lee, G.S., Y.W. Choi, M.H. Lee, S.G. Kim, and G.S. Choi, 2016. Reconnaissance surveying for cultural assets using Unmanned Aerial Vehicle, Journal of the Korean Cadastre Information Association, 18(3): 25-34 (in Korean with English abstract). |
7 | Lee, I.S., M.K. Lee, J.H. Kang, and J.O. Lee, 2013. Application of ultra-light UAV in cadastre, Proc. of 2013 Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Busan, Apr. 25-26, pp. 181-183 (in Korean with English abstract). |
8 | Na, S.I., J.H. Park, and J.K. Park, 2012. Development of Korean Paddy Rice Yield Prediction Model (KRPM) using meteorological element and MODIS NDVI, Journal of the Korean Society of Agricultural Engineers, 54(3): 141-148 (in Korean with English abstract). DOI |
9 | Lee, K.D., C.W. Park, K.H. So, and S.I. Na, 2017. Selection of optimal vegetation indices and regression model for estimation of rice growth using UAV aerial images, Korean Journal of Soil Science and Fertilizer, 50(5): 409-421 (in Korean with English abstract). DOI |
10 | Louhaichi, M., M.N. Borman, and D.E. Johnson, 2001. Spatially located platform and aerial photography for documentation of grazing impacts on wheat, Geocarto International, 16(1): 65-70. DOI |
11 | Na, S.I., S.Y. Hong, Y.H. Kim, and K.D. Lee, 2014. Estimation of corn and soybean yields based on MODIS data and CASA model in Iowa and Illinois, USA, Korean Journal of Soil Science and Fertilizer, 47(2): 92-99 (in Korean with English abstract). DOI |
12 | Na, S.I., C.W. Park, and K.D. Lee, 2016a. Application of highland kimchi cabbage status map for growth monitoring based on unmanned aerial vehicle, Korean Journal of Soil Science and Fertilizer, 49(5): 469-479 (in Korean with English abstract). DOI |
13 | Na, S.I., C.W. Park, Y.J. Kim, and K.D. Lee, 2016b. Mapping the spatial distribution of IRG growth based on UAV, Korean Journal of Soil Science and Fertilizer, 49(5): 495-502 (in Korean with English abstract). DOI |
14 | Na, S.I., C.W. Park, Y.K. Cheong, C.S. Kang, I.B. Choi, and K.D. Lee, 2016c. Selection of optimal vegetation indices for estimation of barley & wheat growth based on remote sensing - An application of unmanned aerial vehicle and field investigation data, Korean Journal of Remote Sensing, 32(5): 483-497 (in Korean with English abstract). DOI |
15 | Na, S.I., C.W. Park, K.H. So, J.M. Park, and K.D. Lee, 2017c. Satellite imagery based winter crop classification mapping using hierarchical classification, Korean Journal of Remote Sensing, 33(5-2): 677-687 (in Korean with English abstract). DOI |
16 | Na, S.I., S.Y. Hong, C.W. Park, K.D. Kim, and K.D. Lee, 2016d. Estimation of highland kimchi cabbage growth using UAV NDVI and agro-meteorological factors, Korean Journal of Soil Science and Fertilizer, 49(5): 420-428 (in Korean with English abstract). DOI |
17 | Na, S.I., B.K. Min, C.W. Park, K.H. So, J.M. Park, and K.D. Lee, 2017a. Development of field scale model for estimating garlic growth based on UAV NDVI and meteorological factors, Korean Journal of Soil Science and Fertilizer, 50(5): 422-433 (in Korean with English abstract). DOI |
18 | Na, S.I., C.W. Park, K.H. So, J.M. Park, and K.D. Lee, 2017b. Monitoring onion growth using UAV NDVI and meteorological factors, Korean Journal of Soil Science and Fertilizer, 50(4): 306-317 (in Korean with English abstract). DOI |
19 | Na, S.I., Y.J. Kim, C.W. Park, K.H. So, J.M. Park, and K.D. Lee, 2017d. Evaluation of feed value of IRG in middle region using UAV, Korean Journal of Soil Science and Fertilizer, 50(5): 391-400 (in Korean with English abstract). DOI |
20 | Park, J.H. and S.I. Na, 2005. Estimating the vegetation indices for field crops using a spectral reflectance technique, Journal of Agriculture Science Chungbuk National University, 22(1): 101-105 (in Korean with English abstract). |
21 | Park, J.K., A. Das, and J.H. Park, 2015. Application trend of unmanned aerial vehicle (UAV) image in agricultural sector: Review and proposal, Korean Journal of Agricultural Science, 42(3): 269-276 (in Korean with English abstract). DOI |
22 | Simonneaux, V., B. Duchemin, D. Helson, S. Er-Raki, A. Olioso, and A. Chehbouni, 2008. The use of high-resolution image time series for crop classification and evapotranspiration estimate over an irrigated area in central morocco, International Journal of Remote Sensing, 29(1): 95-116. DOI |
23 | Park, M.H., S.G. Kim, and S.Y. Choi, 2013. The Study about building method of geospatial informations at construction sites by Unmanned Aircraft System (UAS), Journal of the Korean Cadastre Information Association, 15(1): 145-156 (in Korean with English abstract). |
24 | Pearson, R.L. and L.D. Miller, 1972. Remote mapping of standing crop biomass for estimation of the productivity of the shortgrass prairie, Proc. of the Eighth International Symposium on Remote Sensing of Environment, Ann Arbor, MI, Oct. 2-6, pp. 1357-1381. |
25 | Qi, J., A. Chehbouni, A.R. Huete, Y.H. Kerr, and S. Sorooshian, 1994. A modified soil adjusted vegetation index, Remote Sensing Environment, 48(2): 119-126. DOI |
26 | Rondeaux, G., M. Steven, and F. Baret, 1996. Optimization of soil-adjusted vegetation indices, Remote Sensing of Environment, 55(2): 95-107. DOI |
27 | Rouse, J.W., R.H. Haas, J.A. Schell, and D.W. Deering, 1974. Monitoring vegetation systems in the great plains with ERTS, Proc. of Third Earth Resources Technology Satellite-1 Symposium, Washington, D.C., pp. 309-317. |
28 | Terry, N., L.J. Waldron, and S.E. Taylor, 1983. The growth and functioning of leaves I, Leaf growth and the development of function, Cambridge University Press, Cambridge, UK. |
29 | Tucker, C.J., 1979. Red and photographic infrared linear combinations for monitoring vegetation, Remote Sensing of Environment, 8(2): 127-150. DOI |
30 | Vincini, M., E. Frazzi, and P. D'Alessio, 2008. A broad-band leaf chlorophyll index at the canopy scale, Precision Agriculture, 9(5): 303-319. DOI |
31 | Dash, J. and P.J. Curran, 2004. The MERIS terrestrial chlorophyll index, International Journal of Remote Sensing, 25(23): 5403-5413. DOI |
32 | Ahn, K.H., Y.H. Park, H.R. En, H.K. Lee, K.H. Lee, I.K. Hwang, and J.Y. Choi, 2014. Atmospheric aerosol measurement using UAV, Proc. of the 57th Meeting of Korean Society for Atmospheric Environment, Pyeongchang, Oct. 30-31, pp. 149. |
33 | Antonarakis, A., K.S. Richards, and J. Brasington, 2008. Object-based land cover classification using airborne LiDAR, Remote Sensing of Environment, 112(6): 2988-2998. DOI |
34 | Broge, N.H. and E. Leblanc, 2000. Comparing predictive power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density, Remote Sensing of Environment, 76(2): 156-172. DOI |
35 | Daughtry, C.S.T., C.L. Walthall, M.S. Kim, E. Brown de Colstoun, and J.E. McMurtrey, 2000. Estimating corn leaf chlorophyll concentration for leaf and canopy reflectance, Remote Sensing of Environment, 74(2): 229-239. DOI |
36 | Eitel, J.U.H., D.S. Long, P.E. Gessler, and A.M.S. Smith, 2007. Using in situ measurements to evaluate the new RapidEyeTM satellite series for prediction of wheat nitrogen status, International Journal of Remote Sensing, 28(18): 4183-4190. DOI |
37 | Gitelson, A.A., Y.J. Kaufman, and M.N. Merzlyak, 1996. Use of a green channel in remote sensing of global vegetation from EOS-MODIS, Remote Sensing of Environment, 58(3): 289-298. DOI |
38 | Eitel, J.U.H., D.S. Long, P.E. Gessler, and E.R. Hunt, 2008. Combined spectral index to improve ground-based estimates of nitrogen status in dryland wheat, Agronomy Journal, 100(6): 1694-1702. DOI |
39 | Franklin S. and M. Wulder, 2002. Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas, Progress in Physical Geography, 26(2): 173-205. DOI |
40 | Gitelson, A.A. and M.N. Merzlyak, 1994. Quantitative estimation of chlorophyll using reflectance spectra: experiments with autumn chestnut and maple leaves, Journal of Photochemistry and Photobiology B: Biology, 22(3): 247-252. DOI |
41 | Gitelson, A.A., Y.J. Kaufman, R. Stark, and D. Rundquist, 2002. Novel algorithms for remote estimation of vegetation fraction, Remote Sensing of Environment, 80(1): 76-87. DOI |
42 | Gitelson, A.A., Y. Gritz, and M.N. Merzlyak, 2003. Relationships between leaf chlorophyll content and spectral reflectance algorithms for non-destructive chlorophyll assessment in higher plants, Journal of Plant Physiology, 160(3): 271-282. DOI |
43 | Haboudane, D., J.R. Miller, N. Tremblay, P.J. Zarco-Tejada, and L. Dextraze, 2002. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture, Remote Sensing of Environment, 81(2-3): 416-426. DOI |
44 | Haboudane, D., J.R. Miller, E. Pattey, P.J. Zarco-Tejada, and I.B. Strachan, 2004. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture, Remote Sensing of Environment, 90(3): 337-352. DOI |
45 | Huete, A., K. Didan, T. Miura, E.P. Rodriguez, X. Gao, and L.G. Ferreira, 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sensing of Environment, 83(1-2): 195-213. DOI |
46 | Haboudane, D., N. Tremblay, J.R. Miller, and P. Vigneault, 2008. Remote estimation of crop chlorophyll content using spectral indices derived from hyperspectral data, IEEE Transactions on Geoscience and Remote Sensing, 46(2): 423-437. DOI |
47 | Hong, S.Y., Y.H. Kim, E.Y. Choe, Y.S. Zhang, Y.K. Sonn, C.W. Park, K.H. Jung, B.K. Hyun, S.K. Ha, and K.C. Song, 2010. Geographic information system and remote sensing in soil science, Korean Journal of Soil Science and Fertilizer, 43(5): 684-695 (in Korean with English abstract). |
48 | Hong, S.Y., J.T. Lee, S.K. Rim, W.K. Jung, and I.S. Jo, 1998. Estimation of paddy rice growth increment by using spectral reflectance signature, Korean Journal of Remote Sensing, 14(1): 83-94 (in Korean with English abstract). DOI |
49 | Huete, A.R., 1988. A soil-adjusted vegetation index (SAVI), Remote Sensing of Environment, 25(3): 295-309. DOI |
50 | Huete, A., C. Justice, and W. Leeuwen, 1999. MODIS vegetation index (MOD13) algorithm theoretical basis document version 3, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA. |
51 | Hunt, E.R., C.S.T. Daughtry, J.U.H. Eitel, and D.S. Long, 2011. Remote sensing leaf chlorophyll content using a visible band index, Agronomy Journal, 103(4): 1090-1099. DOI |
52 | Hunt, E.R., P.C. Doraiswamy, J.E. McMurtrey, C.S.T. Daughtry, E.M. Perry, and B. Akhmedov, 2012. A visible band index for remote sensing leaf chlorophyll content at the canopy scale, International Journal of Applied Earth Observation and Geoinformation, 21: 103-112. |
53 | Jeong, A.C. and K.S. Jung, 2014. Research trend of UAV for flood monitoring, Proc. of 2014 Korean Society of Civil Engineers, Daegu, Oct. 22-24, pp. 907-908. |
54 | Haboudane, D., J.R. Miller, E. Pattey, P.J. Zarco-Tejada, and I.B. Strachan, 2004. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture, Remote Sensing of Environment, 90(3): 337-352. DOI |